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0answers
15 views

Determining the uncertainty of an exponential fit

My problem should probably be built up from the beginning, so lets start there. I performed a certain experiment 25 times. Every time, the experiment consists of 5000 measurements, and each ...
0
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0answers
24 views

How to interpret log-likelihood outputs from MASS::fitdistr (R)

AIM: Fit the best distribution to columns in a dataset (30k records) so that I can to go on to produce test data that is in a similar distribution. WHAT I'VE DONE SO FAR: Using R, I have found and ...
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0answers
20 views

Back Transforming Rates in Poisson GLM with Box and Cox Transformation

Suppose I have fitted a Poisson GLM to model rates as follows: > fit.1=glm(response~X1+X2+ offset(log(population)),family=poisson,data=...) I can get the ...
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0answers
12 views

Confidence interval for fit to poisson count data, for beginner

I have the following graph, which I then normalise and attempt to fit to. The data is a histogram of counts at a given time. The fit then looks like: The issue is that the parameters ...
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0answers
21 views

Error bar for Poisson count data

I have a set of data, counts versus time. The whole data looks like this Here is a sample ...
4
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0answers
77 views
+100

How to fit this neuron firing model with R?

I originally posted this as an answer elsewhere but in retrospect it seems more like a question: What is the sample-size range for which the median should be preferred to the mean as a measure of ...
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1answer
35 views

Fitting logistic function with pymc

I've asked this question on stackoverflow too, but no answer yet. This seems a more appropariate place to ask this question: I'm messing around with pymc to understand it a bit better. Now I am ...
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0answers
27 views

Connection between power law and Zipf's law

I am trying to better understand the connection between the power law distribution and Zipf's distribution (law). There is a neat explanation in [1]. The article suggests that as we can derivate the ...
4
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1answer
168 views

Which distribution fits data better?

I use fitdistr in R to select which distribution fits my data best. I tried cauchy, ...
1
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0answers
124 views

Fitting ARMA model with MATLAB R2012b

I want to fit an ARMA model on a time series (quarterly log returns of a 10 year bond) using MATLAB R2012b. This is part of an exercise. I have problems with the code and the interpretation of a ...
0
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0answers
10 views

Testing parameter estimates

If I have derived parameter estimates for a distribution for some data, do I need to conduct a significance test on these to determine how valid they are? Or is the same effect done by just performing ...
2
votes
1answer
59 views

Fitting a copula with Poisson marginals to data in R

First off, I know this is a question which requires an thorough answer, so I am coming here with a very humble attitude. I have limited knowledge about both copulas and R, so I will try to explain ...
1
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1answer
77 views

t-distribution parameter estimation

I know there are already several threads on this, but none seem to explicitly cover what I want. I have a set of financial data (pulled straight from Bloomberg) and am trying to fit a t-distribution ...
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0answers
49 views

Warnings in R after “fitdistr” used

I have just tried to fit a t-dist in R for some data, and did this by reading in a 21x1 csv file and converting to numeric (can show code used if you think it's important). It has produced parameters ...
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0answers
25 views

Fitting a Non-Central t-Distribution with Location and Scale Transformations

I am trying to fit a distribution function to empirical observations that have the following properties: Non-zero mean Non-unit variance Heavy tails Asymmetric about the mode I am considering ...
2
votes
1answer
71 views

Parameter fitting with STAN?

I have a model that produces data given a set of parameters. Now, given data, I'ld like to find out which parameters of the model are likely. I have an implementation in Matlab that uses Delayed ...
5
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1answer
63 views

Fitting distribution to spatial data

Cross posting my question from mathoverflow to find some stats specific help. I am studying a physical process generating data which projects nicely into two dimensions with non-negative values. ...
1
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0answers
22 views

Fitting of bivariate data to a self-defined probability density function

I have a bivariate set of data points which I want to fit to a self-defined distribution (i.e. not standard normal or chi-square or like that, a different, let's say "new" density function). I would ...
1
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1answer
56 views

Chi-squared Goodness of Fit - very small expected values

I am trying to calculate chi-squared value for my fitted data using: $$ \chi^2 = \sum_i^n{\frac{(y-f(x))^2}{f(x)}} $$ where $f(x)$ are theoretical values from fitted function and $y$ are ...
2
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2answers
67 views

Fit power law for distributions with zeroes

I am pretty new to statistics and have some data that I think may follow a power-law distribution. However, it includes zeroes. I understand that mathematically zeroes can't work, but conceptually, ...
2
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1answer
116 views

Why am I not able to fit a zero inflated poisson distribution?

Following what is suggested here http://stackoverflow.com/questions/7157158/fitting-a-zero-inflated-poisson-distribution-in-r ...
3
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0answers
104 views

Bootstrapping fits to a small sample

I have a sample of experimentally measured survival times that are quite noisy and vary stochastically. The survival probability of these events (number of events with a survival time of t or more) is ...
1
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2answers
78 views

Occam's razor (when is it appropriate to add another free parameter?)

So if I fit data to a function you can almost always decrease $\chi_{\nu}^2$ by adding more free parameters. However, this becomes ridiculous if you are fitting a 100-order polynomial to a straight ...
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0answers
20 views

Appropriateness of applying a fitted model to a different (but similar) set of predictor variables

I have fitted a model of current species habitat suitability as a function of mean annual temperature (MAT) and precipitation (MAP) by regressing the distribution of known occurrences of a species ...
1
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0answers
36 views

Fitting a “pseudo” discrete dataset

I'm working with a dataset that contains information about consumption of apples. The dataset contains the amount of apple consumed in g/day. The problem with this is that the data points fall into 3 ...
2
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1answer
61 views

Zero inflate models vs generalized mixture model

Hi I am looking to compare the fit of a zero- inflated mixture model and a poisson mixture model, the random effects in both models are different. Comparing the fitted values of both models ignores ...
0
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0answers
23 views

How to combine two fitted variables

I have fitted two (and probably more) sets of data to a model using least-squares regression. So I've got the parameter values together with their errors and a reduced chi-squared for both. The data ...
3
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1answer
236 views

ARIMA vs ARMA on the differenced series

In R (2.15.2) I fitted once an ARIMA(3,1,3) on a time series and once an ARMA(3,3) on the once differenced timeseries. The fitted parameters differ, which I attributed to the fitting method in ARIMA. ...
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3answers
178 views

Fitting data to describe data the best way

This data is for a company who wants to minimize their expenses. The expenses is described out of the production costs . (Production, salary, capital and material prices). I need to create a ...
0
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1answer
30 views

Method for estimating (thermodynamic) scaling fit parameters

Let's say I have some measurements, label them $N$, which depend on the variables $x$ and $y$. Further, I hypothesize that there is a scaling relationship between $N$, $x$, and $y$ of the form ...
0
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0answers
95 views

How can I estimate optimal cut-off using linear regression-models

To build two linear regression model, (dependant var : B, independant vars : A1, A2, A3) I have to set the cut point of A1. (high A1 and low A2) I want to pick up the model*s*(a model for high A1, and ...
1
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2answers
60 views

Fitting distribution to a given data

I have a loss data arising out of Operation risk for some particular bank. The standard procedure for arriving at the capital charge w.r.t. Operational risk needs I fit some continuous distribution to ...
2
votes
1answer
201 views

Kolmogorov-Smirnov test strange output

I am trying to fit my data to the one of the continuous PDF (I suggest it to be gamma- or lognormal-distributed). The data consists of about 6000 positive floats. But the results of the ...
1
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1answer
49 views

How to interpret BIC

I am fitting two different models to the same data. In one model, there is one free parameter for three different experimental conditions. In another model, I fit three free parameters, one for each ...
4
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0answers
55 views

Is there anything special about Gamma distribution with the shape parameter k=e?

Is there any unique property of $\mathrm{Gamma}(k=e, \text{ scale})$ or a Negative binomial distribution with $r=e$? Here, $e$ is Euler's number, $e \approx 2.71828$. The reason I'm asking is that ...
2
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2answers
57 views

Parameter confidence intervals which include errors in data

My question seems to be very basic one but my search has not given any similar question. I have small dataset of 8 $(x,y)$ values with uncertainties for $y$ (dependent variable) and the theory ...
1
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1answer
582 views

Fit a regression line by using `MATLAB`

I have the following data ...
4
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0answers
71 views

Difficulty with MCMC implementation

I could really use some guided help! I'm having difficulty understanding an MCMC implementation in terms of modeling a data set. I'm working on generating parameters from stellar light curves, and was ...
4
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2answers
1k views

When fitting a curve, how do I calculate the 95% confidence interval for my fitted parameters?

I am fitting curves to my data to extract one parameter. However, I am unsure what the certainty of that parameter is and how I would calculate / express its $95$% confidence interval. Say for a ...
1
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1answer
212 views

What is fitted in a GARCH: residual or log-return?

Given a time-series of log-return of SP500, then to obtain the volatility process what should we do? Some people say that we need using the ARMA model to withdraw the residual series, then plug this ...
1
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0answers
42 views

How to combine the chi-square distributions (with one model parameter) of many items in a sample?

I have a sample of items, for each of which I have fitted models to obtain the best-fitting ($\chi^2$-minimising) value of a parameter $\alpha$. So for each, I have the values of $\chi^2_i(\alpha)$ ...
5
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0answers
96 views

When an analytical Jacobian is available, is it better to approximate the Hessian by $J^TJ$, or by finite differences of the Jacobian?

Let's say I'm computing some model parameters my minimizing the sum squared residuals, and I'm assuming my errors are Gaussian. My model produces analytical derivatives, so the optimizer does not need ...
2
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2answers
50 views

Fitting a back-to-back distribution

This may be a very simple question, but what does it mean "to fit a back-to-back Weibull distribution" to a residual series (or I suppose, to any arbitrary data)? I think it means to fit a series ...
1
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2answers
128 views

What distribution is suited to modelling the difference between bus schedule and arrival times?

I am looking for a one-dimensional distribution that can be fit to bus-delays. The data are real numbers (positive and negative), and exhibit both skewness and kurtosis. Which distribution should I ...
3
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1answer
194 views

Estimating parameters for shifted Poisson distribution

Suppose I have a data vector v, in which all values are greater than zero. Now, I want to see if it follows a shifted Poisson distribution. Can I do it by ...
4
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1answer
149 views

Can I use Principal Curves Analysis to fit a Vector Cloud instead of a Point Cloud?

I have recently discovered Principal Curves while trying to solve the problem I will describe below. The principle of Principal Curves is to fit a cloud point to find the "path" running along that ...
0
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0answers
234 views

improving fitting results of neural network

I've trained fitnet network for prediction steel's yield stress with MATLAB ann toolbox. The neural network should predict yield stress. I have about 250 vector ...
1
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0answers
111 views

Histogram PDF Fitting - bin Variance Poisson or not

So my basic query is just because you've binned and counted the data into a histogram are the error bars on the bins necessarily the Poisson $\sqrt{N}$? Longer explanation: I have an image of pixel ...
3
votes
1answer
112 views

Fitting different models to my data in R

I have number of seeds fallen at different distances. I need to know which model fits these data, if any model does. There are different models that have been used to fit these data: negative ...
8
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2answers
206 views

Standard errors of hyperbolic distribution estimates using delta-method?

I want to calculate the standard errors of a fitted hyperbolic distribution. In my notation the density is given by \begin{align*} ...